Continual Learning (CL), also called lifelong learning or online machine learning, is the ability of a model to learn continually from an inﬁnite stream of data, gradually integrating new acquired knowledge into old knowledge [1]}.
Continual Learning highlights the sequential nature of the learning process. Formally, newly acquired data is passed to the model in the form of tasks. Tasks are made of labeled classes, uniquely identified and disjoint from each other, and a corresponding dataset. A model then learns sequences of tasks. At each training session, a model has only access to the current task (and possibly to some data kept from previous tasks), which is not accessible anymore after training.
